Open AccessAnt Colony Solving Multiple Constraints Problem: Vehicle Route Allocation
Author(s) -
Sorin C. Negulescu,
Claudiu Vasile Kifor,
Constantin Oprean
Publication year - 2008
Publication title -
international journal of computers communications and control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.422
H-Index - 33
eISSN - 1841-9844
pISSN - 1841-9836
DOI - 10.15837/ijccc.2008.4.2404
Subject(s) - travelling salesman problem , ant colony optimization algorithms , vehicle routing problem , computer science , mathematical optimization , quadratic assignment problem , section (typography) , graph , extremal optimization , ant colony , combinatorial optimization , metaheuristic , routing (electronic design automation) , algorithm , mathematics , theoretical computer science , meta optimization , computer network , operating system
Ant colonies are successfully used nowadays as multi-agent systems (MAS) to solve difficult optimization problems such as travelling salesman (TSP), quadratic assignment (QAP), vehicle routing (VRP), graph coloring and satisfiability problem. The objective of the research presented in this paper is to adapt an improved version of Ant Colony Optimisation (ACO) algorithm, mainly: the Elitist Ant System (EAS) algorithm in order to solve the Vehicle Route Allocation Problem (VRAP). After a brief introduction in the first section about MAS and their characteristics, the paper presents the rationale within the second section where ACO algorithm and its common extensions are described. In the approach (the third section) are explained the steps that must be followed in order to adapt EAS for solving the VRAP. The resulted algorithm is illustrated in the fourth section. Section five closes the paper presenting the conclusions and intentions.
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